Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Monash University
- The University of Queensland
- University of New South Wales
- University of Melbourne
- Macquarie University
- University of Sydney
- Curtin University
- ADELAIDE UNIVERSITY
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- Flinders University
- James Cook University
- RMIT UNIVERSITY
- RMIT University
- The University of Western Australia
- UNIVERSITY OF MELBOURNE
- CHARLES STURT UNIVERSITY
- Charles Sturt University
- FLINDERS UNIVERSITY
- La Trobe University
- MONASH UNIVERSITY
- UNIVERSITY OF SYDNEY
- UNIVERSITY OF WESTERN AUSTRALIA
- University of Tasmania
- 14 more »
- « less
-
Field
-
Research Fellow – AI/Machine Learning in Pharmaceutical Data Job No.: 697007 Location: Clayton campus Employment Type: Full-time Duration: 11-month fixed-term appointment Remuneration: $86,195
-
for Academic Performance . About You You will demonstrate: Completion of a PhD in computer science, cyber security, human-computer interaction, or a closely related discipline with a focus on privacy, provenance
-
passion for applying advanced machine learning to real-world medical challenges. If you thrive in collaborative, multi-disciplinary environments and possess a strong technical foundation in AI methodologies
-
in robotics, machine learning, battery systems or a related discipline to deliver project outcomes, build productive research partnerships and contribute to high-quality outputs. You will have the
-
your expertise in robotics, machine learning, battery systems or a related discipline to deliver project outcomes, build productive research partnerships and contribute to high-quality outputs. You will
-
, and collaborative development experience with artificial intelligence or machine-learning tools and methods, particularly their application to mathematical research or software development. This may
-
, data processing pipelines, machine learning and generative AI applied to physical activity and sleep research. The position will contribute to the development of an AI-based behaviour change tool and
-
, privacy-preserving technologies, adversarial machine learning, explainable AI, or secure software engineering. Collaborate and Translate: Work within a supportive team, present findings at national and
-
are particularly interested in: machine learning for molecular and omics data, including representation learning for biological sequences and structures, and the integration of multiple omics layers machine learning
-
research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research